Value Error Obtained while creating a new dataframe which contains the min and max of a particular column

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I have a data frame as shown below.I need to find the min and max of the column "Chip_Current[uAmp]" I used the below code to create a new data frame but obtained an error.

ValueError: 2 columns passed, passed data had 1 columns.

data = [[DEEP_SLEEP_PVT['Chip_Current[uAmp]'].min()], [DEEP_SLEEP_PVT['Chip_Current[uAmp]'].max()]]
df_DS = pd.DataFrame(data, columns = ['MIN', 'MAX'])

DEEP_SLEEP_PVT is my pivot table name

After running the code provided by Jerzel output is coming as expected. Please see below.

enter image description here

enter image description here

pandas dataframe python
1 Answers

Use Series.aggregate, output is Series, so for one row DataFrame convert it to DataFrame and transpose:

df1 = DEEP_SLEEP_PVT['Chip_Current[uAmp]'].agg(['min','max']).to_frame().T

If need minimal and maximal per some another column/level like Device_ID use GroupBy.agg:

df2 = DEEP_SLEEP_PVT.groupby('Device_ID')['Chip_Current[uAmp]'].agg(['min','max'])

Or by multiple columns/levels:

df3 = (DEEP_SLEEP_PVT.groupby(['Device_ID', 'Temp(deg)'])['Chip_Current[uAmp]']
                     .agg(['min','max']))

Sample data:

DEEP_SLEEP_PVT = (pd.DataFrame({'Chip_Current[uAmp]':[5,0,-1,2,3,2,1,-5,7,4.8],
                               'Device_ID':['FF_2646'] * 5 + ['TT_2438'] * 5,
                               'Temp(deg)':[-20]*3 + [25] * 2 + [-20]*3 + [25] * 2})
                    .set_index(['Device_ID','Temp(deg)']))
    
print (DEEP_SLEEP_PVT)
                     Chip_Current[uAmp]
Device_ID Temp(deg)                    
FF_2646   -20                       5.0
          -20                       0.0
          -20                      -1.0
           25                       2.0
           25                       3.0
TT_2438   -20                       2.0
          -20                       1.0
          -20                      -5.0
           25                       7.0
           25                       4.8

df1 = DEEP_SLEEP_PVT['Chip_Current[uAmp]'].agg(['min','max']).to_frame().T
print (df1)
                    min  max
Chip_Current[uAmp] -5.0  7.0

df2 = DEEP_SLEEP_PVT.groupby('Device_ID')['Chip_Current[uAmp]'].agg(['min','max'])
print (df2)
           min  max
Device_ID          
FF_2646   -1.0  5.0
TT_2438   -5.0  7.0

df3 = DEEP_SLEEP_PVT.groupby(['Device_ID', 'Temp(deg)'])['Chip_Current[uAmp]'].agg(['min','max'])
print (df3)
                     min  max
Device_ID Temp(deg)          
FF_2646   -20       -1.0  5.0
           25        2.0  3.0
TT_2438   -20       -5.0  2.0
           25        4.8  7.0
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